Founded in 2012 in Mexico, Kueski can claim to be the leading local online lending platform designed to offer unsecured loans through direct deposits to clients’ bank accounts or purchases through their tool. The company’s platform leverages several data points to build credit risk and fraud risk machine learning models that will approve or reject loan applications quickly, enabling clients to cover their short-term cash or purchase needs anywhere, including in-store, in the case of BNPL transactions.
At its core, Kueski features a real-time credit system operating at scale, making millisecond decisions at checkout using behavioural and proprietary signals across tens of millions of loans. Jaime Romero, CTO at Kueski, tells RBI how real-time credit decisioning systems are built under latency constraints, why traditional scoring breaks down in emerging markets, discusses the convergence of fraud and credit risk in digital environments and what actually changes when these systems operate at scale.
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RBI: Can you summarise the Kueski value proposition?
Jaime Romero, CTO, Kueski: Mexico is one of the world’s largest consumer markets, yet more than half of its adult population remains outside the formal financial system. That’s not a niche gap — it’s a structural reality that traditional financial institutions have not been designed to address. Kueski was built specifically for that context. Our value proposition is simple: use technology and AI to make financial services faster, safer, and genuinely accessible to consumers who have historically been excluded — not as an afterthought, but as the core design principle.
What makes our approach different is that we didn’t start from traditional lending and add technology on top — we built infrastructure from the ground up for local consumer behaviour, alternative data environments, and a market where millions of people have real purchasing power but no credit history. That means proprietary risk models, real-time decisioning, and a user experience designed for consumers at every stage of their financial journey — from a first loan to a growing credit profile. The result is a platform that today powers credit access for millions of Mexicans and is available across close to 40% of Mexico’s leading e-commerce merchants.
RBI: Kueski launched back in 2012…many firms around the world offering BNPL have failed since then and Kueski itself was loss-making-is it now possible to say that BNPL is a profitable business line?
Romero: At Kueski, our approach has been different from the beginning. We were built as a technology and risk company first, with a strong focus on proprietary underwriting, fraud prevention, and real-time decisioning designed specifically for the Mexican market.
That local understanding matters. Mexico has very different financial dynamics compared to more mature markets — including lower credit penetration, high cash usage, and millions of consumers who remain underserved by traditional financial institutions. At the same time, demand for flexible digital payment solutions continues to grow rapidly, driven by the expansion of e-commerce and changing consumer expectations around accessibility and convenience.
What has differentiated Kueski over the years is our ability to combine deep local market knowledge with technology developed fully in-house. Our AI-driven systems allow us to make more precise risk decisions, adapt quickly to changing market conditions, and operate efficiently at scale. Today, Kueski Pay is available across close to 40% of Mexico’s leading e-commerce merchants, and since our founding we have originated more than 40 million loans. We believe that level of adoption reflects the strength of the model when it is built with long-term sustainability, responsible lending, and local consumer needs at its core
RBI: You have argued that the Kueski credit decisioning systems gives the firm a competitive advantage — can you expand on that?
Romero: Traditional credit systems were designed for markets with mature financial infrastructure and highly standardised consumer data. In Mexico, that approach leaves out a significant portion of the population and often creates a very static view of risk. At Kueski, we’ve built our decisioning infrastructure specifically for the realities of the Mexican market. Instead of relying on a single score or a limited set of variables, our models evaluate thousands of dynamic signals in real time — including behavioural patterns, transactional data, device intelligence, fraud indicators, repayment behaviour, and contextual variables that continuously evolve over time. Because our technology has been developed fully in-house, we can iterate and adapt very quickly. Our models are continuously retrained using repayment outcomes, changing consumer behaviour, seasonality patterns, and broader macroeconomic conditions, allowing us to make more precise and personalised credit decisions at scale
An important part of that advantage is the integration between fraud prevention and underwriting. In digital lending, those systems cannot operate separately. Our infrastructure evaluates both identity confidence and repayment probability simultaneously, helping us improve approval quality while maintaining a seamless user experience. Ultimately, the impact goes beyond speed or automation. Around 20% of our customers report opening a bank account for the first time in order to receive a Kueski loan, which shows how technology can help expand access to the broader financial system.
RBI: What are the major challenges for traditional scoring in emerging markets?
Romero: One of the biggest challenges is that traditional scoring systems were designed for economies where consumers already have long and well-documented financial histories. In markets like Mexico, that assumption often breaks down. Early on at Kueski, we noticed a recurring pattern: consumers with little or no formal credit history were frequently classified as high risk by traditional models, but when given access to small, short-term loans, many of them consistently repaid on time — sometimes more reliably than users with established credit files. The issue wasn’t necessarily that these consumers were riskier. It was that traditional systems were not designed to measure them properly. In emerging markets, a large portion of economic activity happens outside the formal financial system. You have informal income structures, lower banking penetration, limited credit bureau coverage, and financial behaviour that doesn’t always translate cleanly into conventional datasets.
Traditional scoring models also tend to create a relatively static view of risk, relying heavily on historical bureau information while consumer behaviour and economic conditions evolve continuously. That’s where AI-driven systems become important. The challenge is no longer simply access to data but building systems capable of interpreting behaviour under constantly changing conditions. Ultimately, the opportunity is to build financial systems that are more adaptive to the realities of emerging markets and capable of expanding access to consumers who have historically been underserved
RBI: In what ways are Mexicans security concerns shaping consumer behaviour?
Romero: Consumers in Mexico are becoming much more intentional about how they choose digital payment methods. Convenience still matters, but trust and perceived security are increasingly becoming deciding factors in the customer experience. In research conducted by Kueski, 57% of consumers said they are concerned about fraud when shopping online, while 43% reported greater trust in payment methods that do not require sharing bank details directly. Those behaviours reflect a broader shift in how consumers evaluate digital financial products
What we’re seeing is that users increasingly prioritize payment experiences that give them more control, greater transparency, and stronger protection without adding friction to the transaction. This is especially important in markets like Mexico, where many consumers are still building trust in digital financial services. Security is no longer viewed only as a compliance function operating in the background — it has become part of the product experience itself. At Kueski, that has reinforced the importance of building integrated risk infrastructure where fraud prevention, identity verification, and underwriting work together in real time. In high-speed environments like e-commerce and BNPL, those systems cannot operate independently because both are ultimately evaluating whether behaviour appears legitimate under uncertainty. The companies that will lead the next phase of digital payments will be the ones capable of delivering experiences that feel simultaneously seamless, flexible, and secure.
RBI: Does it remain the Kueski plan to go public?
Romero: Going public is a long-term ambition for Kueski, and that hasn’t changed. Right now, our focus is on continuing to grow the business, investing in technology, and expanding access to financial services in Mexico. We believe the best path toward that goal is continuing to build a strong, sustainable business with differentiated technology and disciplined execution.
RBI: What have been some of the company’s most significant milestones?
Romero: Kueski has reached several important milestones that reflect both its scale and continued evolution as a digital financial platform. To date, the company has issued more than 40 million loans in Mexico, supporting millions of consumers and entrepreneurs. Today, Kueski operates the #1 finance app on Android in the country, with close to one million downloads each month. On the ecosystem side, Kueski Pay is now offered by nearly 40% of Mexico’s top e-commerce merchants, including global brands such as Amazon, SHEIN, Adidas, Samsung, and Estée Lauder.
A key milestone has also been the expansion of our AI-driven infrastructure. Today, close to 90% of our interactions with both customers and merchants are handled through virtual assistants, allowing us to operate efficiently at scale while maintaining a high-quality experience.
Kueski has also received strong industry recognition, including being named one of CNBC’s World’s Top FinTech Companies and recognised by AMITAI as Mexico’s most ethical financial company for four consecutive years.
